Blurred Lines: Reimagining the User Experience for Business Intelligence

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Software applications have historically been built with a very specific purpose in mind. Word processors are designed for writing and editing documents, while spreadsheets are for working with numbers. Today’s more modern tools allow you to copy a portion of a spreadsheet and paste it into your written document, or even perform some basic calculations. However, the extent of crossover functionality is limited, and a clear delineation still exists between word processing and spreadsheets.

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Three Keys to Embed Analytics and Create a Money-making Product

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Customers looking to embed Birst into their own product offering often ask, “How can I make money with my data?” It’s a reasonable question for organizations who have invested time and money in a business intelligence platform and now want to know how to leverage their new capabilities to increase revenue. However, the monetization of analytics doesn’t just happen—it takes a strategic approach to create an analytical product that clients are willing to pay for.

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Selling with data – how to make the most of your opportunities

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Sales professionals have seen their roles change massively over the past few years. From being the principal point of contact, to now as one of many sources of information, sales representatives are at a critical juncture of their careers. They need to stand out from the crowd, establish credibility and have a different set of tactics to win. Research by CEB shows that 57% of a purchase decision takes place before any contact with sales, while Sirius Decisions believes this number is even higher, at 67%. As customers are more informed about the wider industry trends and their options, what can sales professionals do to improve their chances of success?

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Birst and Tableau: A Partnership to End Analytical Silos

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Visual discovery tools have transformed the way we think about analytics. They empower people – particularly those without data warehousing experience – to explore data on their own while reducing their dependence on BI experts. Companies like Tableau have defined the benchmark for visual analytics, encouraging vendors to introduce or augment their own data discovery capabilities. This innovation ultimately benefits end users, who today have access to more agile ways to work with data.

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A Blog Series: Adventures in Analytics: Tips on Selecting, Implementing, and Productizing BI Part 3

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In this blog series, I’ve outlined my method of evaluating and implementing analytics projects; providing tips, lessons learned and helpful advice for readers looking for analytics solutions and are in need of a BI vendor. By now, following Part 1 and 2, you will have evaluated qualified BI vendors, moved through the Proof of Concept trials, and made your vendor selection. In Part 3, I’ll provide insight into vendor contracts and, finally, best practices for initial project implementation.

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